| multiway-package {multiway} | R Documentation |
Component Models for Multi-Way Data
Description
Fits multi-way component models via alternating least squares algorithms with optional constraints. Fit models include N-way Canonical Polyadic Decomposition, Individual Differences Scaling, Multiway Covariates Regression, Parallel Factor Analysis (1 and 2), Simultaneous Component Analysis, and Tucker Factor Analysis.
Details
The DESCRIPTION file:
| Package: | multiway |
| Type: | Package |
| Title: | Component Models for Multi-Way Data |
| Version: | 1.0-6 |
| Date: | 2019-03-12 |
| Author: | Nathaniel E. Helwig <helwig@umn.edu> |
| Maintainer: | Nathaniel E. Helwig <helwig@umn.edu> |
| Depends: | CMLS, parallel |
| Description: | Fits multi-way component models via alternating least squares algorithms with optional constraints. Fit models include N-way Canonical Polyadic Decomposition, Individual Differences Scaling, Multiway Covariates Regression, Parallel Factor Analysis (1 and 2), Simultaneous Component Analysis, and Tucker Factor Analysis. |
| License: | GPL (>=2) |
Index of help topics:
USalcohol United States Alcohol Consumption Data
(1970-2013)
congru Tucker's Congruence Coefficient
const.control Auxiliary for Controlling Multi-Way Constraints
corcondia Core Consistency Diagnostic
cpd N-way Canonical Polyadic Decomposition
fitted.cpd Extract Multi-Way Fitted Values
fnnls Fast Non-Negative Least Squares
indscal Individual Differences Scaling
krprod Khatri-Rao Product
mcr Multiway Covariates Regression
meansq Mean Square of Given Object
mpinv Moore-Penrose Pseudoinverse
multiway-package Component Models for Multi-Way Data
ncenter Center n-th Dimension of Array
nscale Scale n-th Dimension of Array
parafac Parallel Factor Analysis-1
parafac2 Parallel Factor Analysis-2
print.cpd Print Multi-Way Model Results
reorder.cpd Reorder Multi-Way Factors
rescale Rescales Multi-Way Factors
resign Resigns Multi-Way Factors
sca Simultaneous Component Analysis
smpower Symmetric Matrix Power
sumsq Sum-of-Squares of Given Object
tucker Tucker Factor Analysis
cpd computes the N-way Canonical Polyadic Decomposition of a tensor. indscal fits the Individual Differences Scaling model. mcr fits the Multiway Covariates Regression model. parafac fits the 3-way and 4-way Parallel Factor Analysis-1 model. parafac2 fits the 3-way and 4-way Parallel Factor Analysis-2 model. sca fits the four different Simultaneous Component Analysis models. tucker fits the 3-way and 4-way Tucker Factor Analysis model.
Author(s)
Nathaniel E. Helwig <helwig@umn.edu>
Maintainer: Nathaniel E. Helwig <helwig@umn.edu>
References
Bro, R., & De Jong, S. (1997). A fast non-negativity-constrained least squares algorithm. Journal of Chemometrics, 11, 393-401.
Bro, R., & Kiers, H.A.L. (2003). A new efficient method for determining the number of components in PARAFAC models. Journal of Chemometrics, 17, 274-286.
Carroll, J. D., & Chang, J-J. (1970). Analysis of individual differences in multidimensional scaling via an n-way generalization of "Eckart-Young" decomposition. Psychometrika, 35, 283-319.
Harshman, R. A. (1970). Foundations of the PARAFAC procedure: Models and conditions for an "explanatory" multimodal factor analysis. UCLA Working Papers in Phonetics, 16, 1-84.
Harshman, R. A. (1972). PARAFAC2: Mathematical and technical notes. UCLA Working Papers in Phonetics, 22, 30-44.
Harshman, R. A., & Lundy, M. E. (1994). PARAFAC: Parallel factor analysis. Computational Statistics and Data Analysis, 18, 39-72.
Haughwout, S. P., LaVallee, R. A., & Castle, I-J. P. (2015). Surveillance Report #102: Apparent Per Capita Alcohol Consumption: National, State, and Regional Trends, 1977-2013. Bethesda, MD: NIAAA, Alcohol Epidemiologic Data System.
Helwig, N. E. (2013). The special sign indeterminacy of the direct-fitting Parafac2 model: Some implications, cautions, and recommendations, for Simultaneous Component Analysis. Psychometrika, 78, 725-739.
Helwig, N. E. (2017). Estimating latent trends in multivariate longitudinal data via Parafac2 with functional and structural constraints. Biometrical Journal, 59(4), 783-803.
Helwig, N. E. (in prep). Constrained parallel factor analysis via the R package multiway.
Hitchcock, F. L. (1927). The expression of a tensor or a polyadic as a sum of products. Journal of Mathematics and Physics, 6, 164-189.
Kiers, H. A. L., ten Berge, J. M. F., & Bro, R. (1999). PARAFAC2-part I: A direct-fitting algorithm for the PARAFAC2 model. Journal of Chemometrics, 13, 275-294.
Kroonenberg, P. M., & de Leeuw, J. (1980). Principal component analysis of three-mode data by means of alternating least squares algorithms. Psychometrika, 45, 69-97.
Moore, E. H. (1920). On the reciprocal of the general algebraic matrix. Bulletin of the American Mathematical Society 26, 394-395.
Nephew, T. M., Yi, H., Williams, G. D., Stinson, F. S., & Dufour, M.C., (2004). U.S. Alcohol Epidemiologic Data Reference Manual, Vol. 1, 4th ed. U.S. Apparent Consumption of Alcoholic Beverages Based on State Sales, Taxation, or Receipt Data. Bethesda, MD: NIAAA, Alcohol Epidemiologic Data System. NIH Publication No. 04-5563.
Penrose, R. (1950). A generalized inverse for matrices. Mathematical Proceedings of the Cambridge Philosophical Society 51, 406-413.
Ramsay, J. O. (1988). Monotone regression splines in action. Statistical Science, 3, 425-441.
Smilde, A. K., & Kiers, H. A. L. (1999). Multiway covariates regression models. Journal of Chemometrics, 13, 31-48.
Timmerman, M. E., & Kiers, H. A. L. (2003). Four simultaneous component models for the analysis of multivariate time series from more than one subject to model intraindividual and interindividual differences. Psychometrika, 68, 105-121.
Tucker, L. R. (1966). Some mathematical notes on three-mode factor analysis. Psychometrika, 31, 279-311.
See Also
CMLS ~~
Examples
# See examples for...
# cpd (Canonical Polyadic Decomposition)
# indscal (INividual Differences SCALing)
# mcr (Multiway Covariates Regression)
# parafac (Parallel Factor Analysis-1)
# parafac2 (Parallel Factor Analysis-2)
# sca (Simultaneous Component Analysis)
# tucker (Tucker Factor Analysis)